Publication Date
In 2025 | 0 |
Since 2024 | 2 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 5 |
Descriptor
Monte Carlo Methods | 5 |
Reliability | 5 |
Structural Equation Models | 5 |
Sample Size | 3 |
Computer Software | 2 |
Error of Measurement | 2 |
Goodness of Fit | 2 |
Simulation | 2 |
Bayesian Statistics | 1 |
Computation | 1 |
Correlation | 1 |
More ▼ |
Source
Structural Equation Modeling:… | 5 |
Author
Elizabeth A. Sanders | 1 |
Green, Samuel B. | 1 |
Hagemann, Dirk | 1 |
Leite, Walter L. | 1 |
Meyerhoff, David | 1 |
Phillip K. Wood | 1 |
Timothy R. Konold | 1 |
Yang, Yanyun | 1 |
Zuo, Youzhen | 1 |
Publication Type
Journal Articles | 5 |
Reports - Evaluative | 3 |
Reports - Research | 2 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Timothy R. Konold; Elizabeth A. Sanders – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Within the frequentist structural equation modeling (SEM) framework, adjudicating model quality through measures of fit has been an active area of methodological research. Complicating this conversation is research revealing that a higher quality measurement portion of a SEM can result in poorer estimates of overall model fit than lower quality…
Descriptors: Structural Equation Models, Reliability, Bayesian Statistics, Goodness of Fit
Phillip K. Wood – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The logistic and confined exponential curves are frequently used in studies of growth and learning. These models, which are nonlinear in their parameters, can be estimated using structural equation modeling software. This paper proposes a single combined model, a weighted combination of both models. Mplus, Proc Calis, and lavaan code for the model…
Descriptors: Structural Equation Models, Computation, Computer Software, Weighted Scores
Leite, Walter L.; Zuo, Youzhen – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Among the many methods currently available for estimating latent variable interactions, the unconstrained approach is attractive to applied researchers because of its relatively easy implementation with any structural equation modeling (SEM) software. Using a Monte Carlo simulation study, we extended and evaluated the unconstrained approach to…
Descriptors: Monte Carlo Methods, Structural Equation Models, Evaluation, Researchers
Yang, Yanyun; Green, Samuel B. – Structural Equation Modeling: A Multidisciplinary Journal, 2010
Reliability can be estimated using structural equation modeling (SEM). Two potential problems with this approach are that estimates may be unstable with small sample sizes and biased with misspecified models. A Monte Carlo study was conducted to investigate the quality of SEM estimates of reliability by themselves and relative to coefficient…
Descriptors: Monte Carlo Methods, Structural Equation Models, Reliability, Sample Size
Hagemann, Dirk; Meyerhoff, David – Structural Equation Modeling: A Multidisciplinary Journal, 2008
The latent state-trait (LST) theory is an extension of the classical test theory that allows one to decompose a test score into a true trait, a true state residual, and an error component. For practical applications, the variances of these latent variables may be estimated with standard methods of structural equation modeling (SEM). These…
Descriptors: Structural Equation Models, Test Theory, Reliability, Sample Size